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An extended STIRPAT model and forecast of carbon emission based on green consumption behaviors: evidence from China

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Abstract

An extended STIRPAT model was constructed to explore the impact of green consumption behaviors on carbon emission. Based on the panel data of 30 provinces in China from 2005 to 2019, this paper analyzed the effect of green consumption behaviors, regional population size, economic development level and technological level on carbon emission, and then forecasted the carbon emission in eastern, central and western China from 2020 to 2035. The results demonstrate that carbon emission increases with the expansion of population size; green consumption behaviors have a significant moderating effect on carbon emission and alleviate the pressure of population growth on carbon emission; instead of following the environmental Kuznets curve, the trend of carbon emission shows an inverted “N” curve with economic growth; There is a positive correlation between technological progress and carbon emission; the increase in the level of consumers’ expenditure and the ratio of the secondary industry output value over the total GDP lead to an increase in carbon emission, while the improvement of the urbanization level reduces carbon emission. Policy implications and prospects are also discussed.

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Data availability

The datasets generated during the current study are available in the National Bureau of Statistics (https://data.stats.gov.cn/), CSMAR Database (https://www.gtarsc.com/), and Carbon Emission Accounts and Datasets (https://www.ceads.net.cn/). And further inquiries can be directed to the corresponding author.

Abbreviations

CEADs:

Carbon emission accounts and datasets

CO2 :

Carbon emission

CS:

Consumption level

CSMAR:

China stock market and accounting research database

DK:

Driscoll and Kraay method

EKC:

Environmental Kuznets curve

FE:

Fixed effect model

GDP:

Gross domestic product

IPAT:

I = P × A × T, I: Environmental capacity, P: population size, A: affluence, T: technology

IPCC:

Intergovernmental panel on climate change

IS:

Industrial structure

LMDI:

Logarithmic mean divisia index

MOST:

Ministry of Science and Technology of the People’s Republic of China

NBS:

National Bureau of Statistics

R&D:

Research and Development

RICE-LEAP:

Regional integrated model of climate and the economy-long-range energy alternatives planning model

STIRPAT:

I = a PbAcTd e, I: Environmental capacity, P: population size, A: affluence, T: technology

UR:

Urbanization level

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Acknowledgements

The authors would like to thank the National Bureau of Statistics, CSMAR Database and Carbon Emission Accounts and Datasets for their data accessibility for this study. The authors wish to extend their sincere thanks to Jack Z Wang for his linguistic assistance during the preparation of this manuscript. The authors sincerely appreciate the professional comments from editors and reviewers.

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  1. School of Management, Hefei University of Technology, Anhui, 230009, China

    Cisheng Wu, Manman Ge, Zhiyuan Huang, Linchuan Wang & Teng Liu

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Cisheng Wu involved in conceptualization, methodology, writing—original draft and writing—review and editing. Manman Ge involved in data curation, methodology, writing—original draft and writing—review and editing. Zhiyuan Huang involved in data curation. Linchuan Wang involved in validation. Teng Liu involved in validation.

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Wu, C., Ge, M., Huang, Z. et al. An extended STIRPAT model and forecast of carbon emission based on green consumption behaviors: evidence from China. Environ Dev Sustain 26, 8955–8977 (2024). https://doi.org/10.1007/s10668-023-03077-4

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